bio-epitranscriptomics-merip-preprocessing

npx skills add majiayu000/claude-skill-registry --skill merip-preprocessing --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# MeRIP-seq Preprocessing ## Alignment with STAR ```bash # Build index (once) STAR --runMode genomeGenerate \ --genomeDir star_index \ --genomeFastaFiles genome.fa \ --sjdbGTFfile genes.gtf # Align IP and input samples for sample in IP_rep1 IP_rep2 Input_rep1 Input_rep2; do STAR --genomeDir star_index \ --readFilesIn ${sample}_R1.fastq.gz ${sample}_R2.fastq.gz \ --readFilesCommand zcat \ --outSAMtype BAM SortedByCoordinate \ --outFileNamePrefix ${sample}_ done ``` ## QC Metrics ```bash # Index BAMs for bam in *Aligned.sortedByCoord.out.bam; do samtools index $bam done # Check IP enrichment # Good MeRIP: IP should have peaks, input should be uniform samtools flagstat IP_rep1_Aligned.sortedByCoord.out.bam ``` ## IP/Input Correlation ```python import deeptools.plotCorrelation as pc # Check replicate correlation multiBamSummary bins \ -b IP_rep1.bam IP_rep2.bam Input_rep1.bam Input_rep2.bam \ -o results.npz plotCorrelation -in results.npz \ --corMethod spearman \ -o correlation.png ``` ## Related Skills - read-qc - Raw read quality assessment - read-alignment - General alignment concepts - m6a-peak-calling - Next step after preprocessing

Build index (once)
STAR --runMode genomeGenerate \
Align IP and input samples
for sample in IP_rep1 IP_rep2 Input_rep1 Input_rep2; do
STAR --genomeDir star_index \
done
Index BAMs
for bam in *Aligned.sortedByCoord.out.bam; do
samtools index $bam
Check IP enrichment